Determinants of customer satisfaction in online grocery shopping
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to investigate the factors that influence consumer satisfaction with e-grocery shopping. Moreover, it also delves into factors that motivate shoppers to buy groceries from online retailers rather than conventional stores. A primary survey was administered to collect data. Initially, 500 questionnaires were circulated to respondents. People who have ordered groceries from online sites were the expected respondents. In this study, convenience sampling was used, and data were analyzed using structural equation modeling (SEM). The findings affirmed the relationship between consumer satisfaction and perceived convenience, risk factors, perceived product quality, and time value. However, perceived value and value for the time have a little significant effect on consumer satisfaction. There have been relatively few academic studies that look at the variables that influence customer satisfaction when shopping for groceries online. Most of the studies look at the variables that influence consumer satisfaction in the life insurance and financial services industries. By analyzing the data from Delhi and the Nation Capital Region (NCR) of Delhi, this research aims to bridge this gap available in the literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it